Particle Filtering Approach for GNSS RAIM and FPGA Implementation

Abstract

The integrity monitoring system, as an integral part of aviation navigation system for global navigation satellite system (GNSS), should detect and isolated Failures or faults caused by system failures to maintain the integrity of the GNSS. The pseudorange residual noise of navigation satellites does not completely follow the Gaussian distribution, the performance of traditional filtering algorithms (such as the Kalman filtering) may be reduced due to non-Gaussian noise. The particle filter algorithm has great advantage to dealing with the nonlinear and non-Gaussian system. in this paper, the particle filter algorithm is applied to GNSS receiver autonomous integrity monitoring(RAIM) to detect the fault of navigation satellite. Firstly, Log likelihood ratio (LLR) testing is established; and then, the consistency between the state estimation of the main particle filter and the auxiliary particle filter is checked to determine whether the navigation satellite has failed; finally, the novel RAIM algorithm is undertaken by field programmable gate array (FPGA), the modules of the proposed RAIM algorithm is implemented. The effectiveness of the proposed approach is illustrated in a problem of GPS (Global Positioning System) autonomous integrity monitoring system, the algorithm and its implementation can be embeded in GNSS receiver.